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Record W4400903413 · doi:10.2196/preprints.64458

Effects of Integrating Wearable Activity Trackers with a Home-based Multi-component Exercise Intervention on Fall-related Parameters and Physical Function in Older Adults: A Randomized Controlled Trial (Preprint)

2024· preprint· en· W4400903413 on OpenAlexaboutno aff
Yejin Kim, Kyung‐Hee Park, Hye‐Mi Noh

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintActivity trackerWearable computerComponent (thermodynamics)Randomized controlled trialIntervention (counseling)Physical medicine and rehabilitationPhysical therapyFunction (biology)Physical activityMedicineGerontologyPsychologyComputer scienceEmbedded systemNursingWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND Older adults with a history of fall often encounter challenges in participating in group exercise programs. Recent technological advances, such as activity trackers, can potentially enhance home-based exercise programs by providing continuous physical activity monitoring and feedback. OBJECTIVE To explore whether integrating wearable activity trackers with a home-based exercise intervention is effective in reducing fear of falling and improving physical function in older adults. METHODS This was a 12-week, parallel-group, randomized controlled trial involving 30 older adults (≥60 years) with a history of fall. Participants were randomly assigned in a 1:1 ratio to either a group combining an activity tracker with a home-based multi-component exercise intervention, which included in-person exercise sessions, exercise videos, and objective feedback via phone calls (AT+EX group) or to a group using the activity tracker only for self-monitoring (AT-only group). The primary and secondary outcomes included fall-related parameters (fear of falling assessed by the Activities-specific Balance Confidence [ABC] and the Falls Efficacy Scale-International [FES-I] scales), depression (Short Geriatric Depression Scale), cognition (Montreal Cognitive Assessment), physical function (grip strength, Short Physical Performance Battery [SPPB], Timed Up and Go [TUG] test, 2-min Step Test [2MST]), and body composition. Changes in the average daily step count were monitored and analyzed. RESULTS Overall, 28 participants (mean age, 74 years; 76.7% women) completed the 12-week follow-up period (28/30, 93%). In the AT+EX group, significant improvements were observed in fear of falling (ABC: P=.002; FES-I: P=.01). The AT-only group also showed a significant improvement in FES-I score (P=.01). Physical function significantly improved in the AT+EX group (SPPB, P=.004; TUG, P=.008; 2MST, P=.001), whereas the AT-only group showed significant improvement only in the TUG test (P=.002). However, no significant between-group differences were observed in the ABC score, FES-I score, or physical function. Despite no significant increase in daily step counts, both groups maintained close to 10,000 steps/d throughout the 12 weeks. CONCLUSIONS Both groups showed improvements in the FES-I and TUG test scores without significant between-group differences. Wearable technology, with or without exercise intervention, seems to be an effective tool in reducing the fear of falling and improving physical function in older adults susceptible to falls. CLINICALTRIAL Clinical Research Information Service KCT0008230

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.280
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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